Why Your Bullet Points Don't Sound Like Your Customer

The number that doesn't add up

Priya sells magnesium gummies. Good reviews, decent star rating, a formula she's genuinely proud of — third-party tested, bioavailable glycinate, no fillers. Her bullets say all of that, clearly and accurately. And her CVR sits stubbornly around 7%, half of what her closest competitor pulls with what Priya considers a worse product.

She's read her own bullets a hundred times. They're correct. They're also, she suspects, not actually working — and she can't tell why, because from the inside, correct and persuasive feel like the same thing.

Why "clearer copy" doesn't fix it

The usual advice here is to tighten the bullets — shorter sentences, more white space, lead with the benefit. Priya tried that. CVR didn't move. That's because the problem isn't clarity. Her bullets are perfectly clear. The problem is that they're written in a vocabulary nobody outside a supplement-industry Slack channel actually uses.

"Bioavailable." "Third-party tested." "Glycinate chelate." These are real, accurate, defensible claims, and they're the words a formulator uses, not the words a tired parent googling "why can't I sleep" reaches for when they're deciding whether to click buy. A shopper doesn't need to understand the chemistry. They need to recognize themselves in the copy. When the words on the page don't match the words in the customer's own head, the listing reads as for someone else — technically true, but not felt.

The diagnosis lens: vocabulary is the gap, not accuracy

This is a Customer-side diagnosis, not a features-side one. The question isn't "is this claim true" — it clearly is. The question is "does this claim sound like something the customer would say about their own problem." Those are different tests, and most founders only ever run the first one, because they wrote the copy from the product outward instead of from the customer inward.

The fix has to start with what customers actually say, in their own words, before touching a single bullet.

The working session

Priya brought the coach her current bullets and a stated goal: find out if the vocabulary was the problem before rewriting anything on a hunch.

The coach ran build_avatar_stage, starting at S1 — the vocabulary stage, which extracts the customer's actual language rather than the brand's language about the customer. This isn't guesswork or a generic buyer-persona template; it pulls from real customer-facing evidence to surface how this specific audience talks about this specific problem.

What the coach said: "Your bullets say 'bioavailable magnesium glycinate.' Nobody in your reviews says that. They say 'actually helps me stay asleep' and 'doesn't upset my stomach like the other kind did.' That second phrase is doing work your copy isn't — it's answering an objection your bullets never raise."

To make sure that vocabulary read held up against something more concrete than a general sense of tone, the coach ran ingest_evidence against Priya's actual review history. The parsed reviews confirmed the pattern at scale: "stomach" and "upset" appeared across a meaningful share of five-star reviews, almost always framed as relief from a bad experience with a different magnesium form. Nobody had mentioned bioavailability once. Not one review.

That's the gap. Priya's bullets were arguing a formulation point. Her customers were relieved about a stomach problem the copy never named.

Rebuilding from real language, not assumption

The rewrite wasn't a tone pass. It was a vocabulary swap grounded in what S1 and the review evidence actually surfaced. "Bioavailable magnesium glycinate" became something closer to "the gentle form that won't upset your stomach like other magnesium can" — same underlying fact, stated in the words a buyer already uses to describe their own relief. The accurate claim didn't change. The language wrapping it did.

This same gap shows up anywhere a founder writes from the inside of their own product knowledge instead of the outside of the customer's actual words. A brand story built for the wrong audience entirely is the same root cause at a bigger scale — speaking fluently to a buyer who isn't the one actually there. And reviews highlighted for the wrong reason show the same pattern in reverse: curating social proof around what the brand thinks matters instead of what customers actually said.

If Priya wants a faster first read on whether her listing has this kind of gap anywhere else, the free trust gap diagnostic takes six questions and flags it without needing the full review-mining pass. Founders further down this road often also find their featured reviews miss the real trigger for the same reason — proof chosen by the brand's logic, not the customer's.

What to measure after

Watch CVR over the next two to three weeks specifically among sessions that reach the bullet section — not just headline CVR, since a vocabulary fix in the bullets won't move a CTR problem elsewhere on the page. If CVR moves without a corresponding change in traffic quality or ad spend, that's the vocabulary swap working. If it doesn't move, the next diagnosis probably isn't vocabulary at all. It's worth running run_trust_gap to check whether a different pillar is the actual weak point.

The one next action

Before rewriting anything, pull ten of your own five-star reviews and highlight every phrase a customer used to describe relief, not the product. Compare that language to your current bullet one. If they don't share a single word, that's your answer.